Location Estimation of a Random Signal Source Based on Correlated Sensor Observations

@article{Sundaresan2011LocationEO,
  title={Location Estimation of a Random Signal Source Based on Correlated Sensor Observations},
  author={A. Sundaresan and P. Varshney},
  journal={IEEE Transactions on Signal Processing},
  year={2011},
  volume={59},
  pages={787-799}
}
  • A. Sundaresan, P. Varshney
  • Published 2011
  • Mathematics, Computer Science
  • IEEE Transactions on Signal Processing
  • The problem of location estimation of a source of random signals using a network of sensors is considered. A novel maximum-likelihood estimation (MLE) based approach using copula functions is proposed. The measurements received at the sensors are often spatially correlated and characterized by a multivariate distribution. Using the theory of copulas, the joint parametric density of sensor observations (joint likelihood) is approximated assuming only the knowledge of the marginal likelihood… CONTINUE READING
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    References

    SHOWING 1-10 OF 37 REFERENCES
    Maximum Likelihood Localization of a Diffusive Point Source Using Binary Observations
    • 51
    • PDF
    A maximum-likelihood parametric approach to source localizations
    • J. Chen, R. Hudson, K. Yao
    • Mathematics, Computer Science
    • 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221)
    • 2001
    • 61
    Target Location Estimation in Sensor Networks With Quantized Data
    • R. Niu, P. Varshney
    • Mathematics, Computer Science
    • IEEE Transactions on Signal Processing
    • 2006
    • 253
    • PDF
    Radiological Source Detection and Localisation Using Bayesian Techniques
    • 46
    Distributed Sequential Bayesian Estimation of a Diffusive Source in Wireless Sensor Networks
    • Tong Zhao, A. Nehorai
    • Mathematics, Computer Science
    • IEEE Transactions on Signal Processing
    • 2007
    • 132
    • PDF
    Detection and Localization of Material Releases With Sparse Sensor Configurations
    • 11
    • PDF
    Channel Aware Target Localization With Quantized Data in Wireless Sensor Networks
    • 110
    • PDF
    Identification of Low-Level Point Radiation Sources Using a Sensor Network
    • N. Rao, M. Shankar, +5 authors J. C. Hou
    • Computer Science
    • 2008 International Conference on Information Processing in Sensor Networks (ipsn 2008)
    • 2008
    • 85
    • PDF
    Detection and parameter estimation of multiple radioactive sources
    • 80
    • PDF